Simulations of spinal cord recruitment to optimize bioelectronic interventions for lower urinary tract control

Lower urinary tract (LUT) dysfunction occurs in 20-40% of the global population and has an economic impact measured in tens of billions of dollars every year in the United States. This field desperately needs new therapies as current treatments, such as clean intermittent catheterization and pharmaceuticals, have significant side effects. Epidural spinal cord stimulation (SCS) provides a potential solution. SCS is a rapidly growing area of bioelectronic medicine, with tens of thousands of implants occurring each year in the United States. While SCS normally activates the dorsal columns, this technique can also be used to recruit primary sensory neurons as they enter the spinal cord through the dorsal rootlets. These sensory inputs play a crucial role in regulating bladder function6 and activating these primary sensory neurons can have powerful effects on bladder behavior. Through ongoing SPARC efforts, our team has established that high-resolution SCS can selectively recruit sacral afferents leading to both micturition and continence reflexes. These data support our ultimate translational goal to develop a SGS therapy to improve bladder function after injury and disease. However, a critical gap remains to understand, develop and optimize these neuromodulation therapies. There are no models that accurately represent the complex sacral spinal anatomy, and previous modelling efforts have consistently ignored the dorsal rootlets. In this project, we will develop functionalized, anatomically accurate models of the cat sacral spinal cord. including the dorsal rootlets, and validate these models using electrophysioloqical data acquired under an existing SPARC effort. Task 1: Create a pipeline for anatomically accurate, ultra-high resolution finite element models of the cat sacral spinal cord Accurate anatomy is critical for biophysical models of stimulation-evoked neural recruitment. However, these structures have been underappreciated in modelling efforts, in part due to their anatomical complexity. We will use diffusion tensor imaging (DTI) and structural magnetic resonance imaging to acquire detailed anatomy of the sacral spinal cord in the cat, including dorsal and ventral rootlet fiber pathways and develop a pipeline within o2S2PARC segment these images and create finite element method (FEM) models of these tissues. Year 1: Imaging dataset of sacral spinal cord in one cat and preliminary pipeline. Year 2: Imaging datasets for four spinal cords to validate anatomical model creation pipeline. Task 2: Create finite element models, functionalized with computational axon models, and validate recruitment using existing electrophysiological data We will use Sim4Life and the o2S2PARC platform to mesh and populate simplified and anatomically accurate spinal cord models with populations of pelvic, pudenda! and sciatic nerve axons that project into the cord. DTI data will be used to create realistic 3D axon trajectories and the model will be validated using existing data (OT2OD024908). Year 1: Functionalized model of simplistic spinal cord and simulated effects of epidural stimulation. Year 2: Functionalized model of anatomically accurate sacral spinal cord with validated recruitment properties. Task 3: Model spinal reflexes that simulate frequency-dependent excitatory and inhibitory bladder activity SCS at different frequencies on the same contact can evoke opposing effects on bladder pressure through spinal reflexes. To model this effect we will extend SCS recruitment models to include, for the first time, computational models of spinal reflexes that reproduce observed behavioral effects. This will create functionalized finite element models that can predict the effects of stimulation frequency on a target organ. Year 1: Reflex model structure defined and coupled to finite element stimulations. Year 2: Completed functional simulations of bladder behavior, driven by SCS, that reproduce frequency-dependent effects. This project will create credible (https://bit.ly/2NFeYLj) open-source and community extensible tools, models and simulations to improve SGS-based neuromodulation therapies to enhance treatments for people living with lower urinary tract dysfunction.